Trite as it may sound, the goal of teaching is for students to learn. The courses I now teach are graduate classes and tailored to that audience. When it makes sense for a subject, I like to emphasize project data, teamwork, writing, and presentation skills. Below I discuss a couple of specific examples.
As an indication of quality, I was ranked 2nd for teaching in the 2010 internal faculty evaluation of the EAS Department, a large group (27) that includes three past winners of the college outstanding teacher award.
Not all teaching is in the classroom, of course. One-on-one work with graduate students is essential and I run two open meetings per week for students I advise. I also maintain a blog with helpful information and notices.
During my 15 years at The University of Tulsa I taught a wide array of courses. These included freshman-level Physical Geology and The Earth in Space (which I developed). Owing to the small faculty size, many courses were taught as mixed undergrad/grad. In this category were Petroleum Seismology, Advanced Petroleum Seismology, Advanced Global Seismology, and Environmental Geophysics. In addition, the courses Advanced Seismic Data Processing and Seismic Stratigraphy where pure graduate classes. The Environmental Geophysics course included field exercises using electrical conductivity and ground-penetrating radar equipment. Most of these graduate courses had less than eight students, while at The University of Houston there were 49 in my spring 2010 Geophysical Data Analysis (largest graduate course in the department). One has to be flexible and patient to deal with these extremes.
At the University of Houston I have been involved in the 2009 and 2011 Geophysical Field Camp held near Red Lodge Montana. My field work at camp has involved 2D and 3D seismic seismic surveys using single and multicomponent receivers and various sources. In the classroom at UH, I routinely teach the graduate classes 3D Seismic Interpretation I (synthetic seismogram, girdding, horizon tracking, faults, prospect generation) and Geophysical Data Processing (the science behind seismic data processing).
Seismic Interpretation I is a good example of how I teach. It would be possible to teach such a class in traditional lecture format, but that would leave the students not ready to do significant work themselves on, say, a thesis project. So I break the class into three major assignments. Each is a mini-workshop lasting 5-7 class periods and involves working with real data in a commercial interpretation system. The hard deadline is intentional to ramp up the sense importance and simulate real-life deadlines for company projects, lease sales, and proposal submission deadlines. The first assignment is not orally presented, but graded for slide style, clarity, logic, and completeness. Assignment 2 is more ambitious, on a shorter deadline, and slide element grading stricter. This process can lead to some truly remarkable improvement in the mechanics of learning sophisticated software and preparing a presentation. The last assignment is to generate a prospect using industry Gulf of Mexico data. Two class periods are used to generate three leads, one of which is chosen at random as 'the prospect'. This project requires fault mapping, structural interpretation, amplitude analysis, reserve estimates, and economics. In the fashion of the industry, prospects are named and will be promoted to an audience. Once the prospect presentations are locked down (deadline again!), each student presents his/her prospect to the class in random order and completes an evaluation form on all other prospects. In a class of 30, this process takes five class periods. At the end of each, the class votes for Best Prospect of the Day. When all presentations are complete, the daily winners give a brief review and the class votes for Best Prospect. To make it fun, daily winners get a small surprise gift and the Best Prospect is awarded a trophy I buy at a local charity thrift store. The fall 2010 Best Prospect was Ambrosia and the trophy was a ceramic owl signifying wisdom. The last requirement of each student is to turn in one evaluation form I randomly specify. Not knowing which will be asked for, they must attend and stay engaged for all presentations.
This is a lot of detail, but the details make teaching effective or not. What does the student have at the end of this course? A respect for deadlines, the ability to jumpstart into complex software, knowledge of petroleum prospecting as well as structural, stratigraphic, and amplitude interpretation of modern 3D seismic data, and tangible evidence of this knowledge in the form of a presentation to show recruiters.
Some classes do not fit into the workshop format. My other recurring graduate class is Geophysical Data Analysis, a survey course on the physics and computing methods behind seismic data processing. The class will open with each student receiving a blank paper on which to write their name and a number called out as we head-count around the room. The papers are collected and I show a list of numbered topics (statics, fractures, velocity analysis, etc.). Thus every student is assigned a random subject and I emphasize that if they have already studied the subject they will get a different one. There are three assignments related to the subject: 1) write an SEG 4-page abstract, 2) prepare a 15 min presentation, and 3) prepare a one-panel poster. For full credit the presented work must include a computational aspect done by the student. Hard deadlines are staged for each item in the order shown. The first 70% of the course is lecture format and the remainder is presentations (again random, with co-evaluation forms, and single random turn-in).
In this way the traditional material is taught along with the method and capability for quickly digging into a new subject (including bibliography, state of the field, recent progress), and students learn to present the new knowledge to a group of peers.
Another theme in my teaching is exposure to open source software. Research often uses powerful commercial software such as Matlab and Mathematica, as well as compiled languages. However, free open source software like SeismicUnix, ImageJ and MeVisLab are launchpads for building custom tools in an advanced development environment. I maintain an open source blog to help students get started.
In summary, I enjoy the variety and constant challenge of teaching, and my methods will continue to evolve.
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